Key points are not available for this paper at this time.
Sarcopenia and chronic pain are prevalent age-related conditions with substantial health impacts, yet their causal relationship remains unclear. Our aim is to study the bidirectional causal relationship among these diseases and identify potential therapeutic targets through genetic methods, as well as explore new therapeutic drugs. We performed bidirectional Mendelian randomization and Bayesian colocalization analyses using GWAS data from sarcopenia and chronic pain studies to explore their genetic relationships. Through integrating PheWAS and DrugBank analyses, we identified potential therapeutic candidates. We then evaluated these candidates using FAERS database for safety profiles and explored their pathway-level associations through drug-omics data. Our analyses revealed significant bidirectional genetic associations between sarcopenia and chronic pain, identifying 9 shared genes ( MAPKAPK3 , MYBPC3 , POLR2L , DDAH1 , FAM177B , ABCC8 , RMDN3 , RFTN2 , and SUOX ). Four genes ( MAPKAPK3 , DDAH1 , ABCC8 , and SUOX ) were identified as druggable targets, with 18 compounds (including approved, investigational, and preclinical drugs) identified as potential therapeutic candidates. After FAERS screened and excluded candidate drugs that might aggravate muscle or pain symptoms, dexlansoprazole and glipizide showed relatively favorable safety profiles among compounds targeting these genes. Subsequent drug-omics analysis identified pathway enrichments consistent with muscle and pain-related processes, though clinical efficacy remains unestablished. This study provides genetic evidence for a causal bidirectional relationship between sarcopenia and chronic pain, identifying potential therapeutic targets. However, findings are based on computational analyses of summary-level data without experimental validation. The identified drug candidates warrant further rigorous experimental and clinical investigation for repurposing strategies in managing these conditions.
Building similarity graph...
Analyzing shared references across papers
Loading...
Juan Li
Sichuan University
J Huang
Sichuan University
Jiang Han
Sichuan University
Medicine
Sichuan University
West China Second University Hospital of Sichuan University
Ministry of Education and Child Care
Building similarity graph...
Analyzing shared references across papers
Loading...
Li et al. (Fri,) studied this question.
synapsesocial.com/papers/6a08aeea280cd4e998e8d9a6 — DOI: https://doi.org/10.1097/md.0000000000048819